Resource Library

Statistics educators are keenly aware of the value of using real data to help students see the relevance and applicability of statistics. The federal statistical agencies have invested in significant efforts to make data accessible and available. In this webinar, Ron Wasserstein will point you to these resources, discussing their uses and limitations.

This four slide animation deals with the difficulty of drawing random samples. The cartoon animation was drawn by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.

Sampling Samba is a video that may be used to discuss and compare various methods of sampling. The methods described include random sampling, systematic sampling, stratified sampling, and cluster sampling. The video was written by Camilla Guatteri (SeeYouGee on You-Tube) and edited by Alessandro Pederzoli.

June 23, 2009 Activity webinar presented and hosted by Leigh Slauson, Otterbein College. This webinar describes an activity that uses the playlist from an iPod music player to teach the concept of random selection, the various sampling techniques, and the use of simulation to estimate probability. The webinar includes a discussion of the background of this activity, the learning goals of the activity, how this activity can be adapted to different levels of technology, suggestions for assessment, and other supplemental reference materials. (handouts and other materials available for free download)

In this hands-on activity, students count the number of chips in cookies in order to carry out an independent samples t-test to see if Chips AhoyŒ¬ cookies have a higher, lower, or different mean number of chips per cookie than a supermarket brand. First there is a class discussion that can include concepts about random samples, independence of samples, recently covered tests, comparing two parameters with null and alternative hypotheses, what it means to be a chip in a cookie, how to break up the cookies to count chips, and of course a class consensus on the hypotheses to be tested. Second the students count the number of chips in a one cookie from each brand, and report their observations to the instructor. Third, the instructor develops the independent sample t-test statistic. Fourth, the students carry out (individually or as a class) the hypothesis test, checking the assumptions on sample-size/population-shape.

By means of a simple story and a worksheet with questions we guide the students from research question to arriving at a conclusion. The whole process is simply reasoning, no formulas. We use the reasoning already done by the student to introduce the standard vocabulary of testing statistical hypotheses (null & alternative hypotheses, p-value, type I and type II error, significance level). Students need to be familiar with binomial distribution tables. After the ducks story is finished, the class is asked to come up with their own research question, collect the data, do the hypotheses testing and answer their own research question. The teaching material is intended to be flexible depending of the time available. Instructors can choose to do just the interactive lecture type, interactive lecture + activity, or even add the optional material.

This activity makes use of a campus-based resource to develop a "capstone" project for a survey sampling course. Students work in small groups and use a complex sampling design to estimate the number of new books in the university library given a budget for data collection. They will conduct a pilot study using some of their budget, receive feedback from the instructor, then complete data collection and write a final report.

Because surveys are increasingly common in the medical literature, readers need to be able to critically evaluate the survey method. Two questions are fundamental: 1) Who do the respondents represent? 2) What do their answers mean? This lecture example discusses survey sampling terms and aspects of interpreting survey results.

This lecture example discusses how two continuous variables relate to one another with a clinical example of the relationship between body mass and fasting blood sugar. It offers three questions to help readers visualize and interpret correlation coefficients.

This activity stresses the importance of writing clear, unbiased survey questions. It explore the types of bias present in surveys and ways to reduce these biases. In addition, the activity covers some basics of surveys: population, sample, sampling frame, and sampling method.